Citation
Yaakob, Razali and Sulaiman, Md. Nasir and Mahmod, Ramlan and Tengku Muda Mohamed, Mahmud and Ramli, Abd Rahman
(1999)
Multi-counterpropagation network model for colour recognition.
Malaysian Journal of Computer Science, 12 (1).
pp. 38-46.
ISSN 0127-9084
Abstract
Minolta Chroma Meters was used to convert colours into numbers. It offers five different colour systems for measuring absolute chromaticity, that is, CIE Yxy, L*a*b*, L*C*H°, Hunter Lab and XYZ. In this study, only L*a*b* is used, and combinations of two counterpropagation network (CPN) are required to recognise 808 colours produced by The Royal Horticultural Society, based on RHS Colour Chart [1]. Our proposed neural network model is tested; the result shows that 99% of trained data are recognised, against 98% for untrained data.
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Official URL or Download Paper: http://e-journal.um.edu.my/publish/MJCS/136-150
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Agriculture Faculty of Computer Science and Information Technology Faculty of Engineering |
| Publisher: | Faculty of Computer Science and Information Technology, University of Malaya |
| Keywords: | CPN model; Competitive layer; Unsupervised learning; Supervised learning; Minolta Chroma Meters |
| Depositing User: | Nabilah Mustapa |
| Date Deposited: | 30 Dec 2016 02:49 |
| Last Modified: | 30 Dec 2016 02:49 |
| URI: | http://psasir.upm.edu.my/id/eprint/49453 |
| Statistic Details: | View Download Statistic |
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